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Fine-tuning of classification models on the BreakHis dataset utilizing the Transformers library from HuggingFace

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BreakHis Fine-Tuning with Transformers

Introduction

This repository focuses on the fine-tuning of models on the BreakHis dataset utilizing the Transformers library from Hugging Face. The BreakHis dataset is an essential resource in the medical imaging domain, particularly for breast cancer histopathological image analysis. Our goal is to harness the power of the Transformers library to enhance the accuracy and efficiency of image processing, thus contributing to advancements in medical diagnostics.

Setup

Prerequisites

Before beginning the setup, ensure you have Conda installed on your system. If Conda is not already installed, you can download and install it from Miniconda or Anaconda.

Dataset

The BreakHis dataset can be downloaded from Kaggle.

Setting up the Environment

  1. Clone the Repository

    Clone this repository to your local machine using the following Git command:

    git clone https://github.com/mikkac/breakhis_vit.git
    cd breakhis_vit
  2. Create a Conda Environment

    Create a new Conda environment with Python 3.11:

    conda create -n breakhis_env python=3.11
    conda activate breakhis_env
  3. Install Dependencies

    Install the required dependencies using pip:

    pip install -r requirements.txt

    Ensure that you have a requirements.txt file in the root of the project directory containing all the necessary packages.

  4. Verify Installation

    Verify the installation by checking the installed packages:

    pip list

Fine-tune

Prepare data

TBA

Run training

TBA

Run evaluation

TBA

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Fine-tuning of classification models on the BreakHis dataset utilizing the Transformers library from HuggingFace

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